This application pertains to the field of telecommunications, and in particular to network management and control systems. Specifically it discloses a real-time, state-dependent network traffic control system for an integrated services telecommunications network capable of handling heterogeneous traffic environments, in which the control strategy is a function of both real-time congestion levels and real-time traffic profiles. The invention includes a predictive algorithm which controls access to the network and routes traffic through the network, while minimizing in real time a weighted function of the projected blocked traffic.
The promise of an Integrated Services Network (ISN) is based, primarily, on three recent developments in the telecommunication industry. The first is the evolution of high capacity network components. Today, fiber optic cables can transmit billions of bits of information per second. Furthermore, the introduction of digital exchanges with multi-rate switching capability of hundreds of thousands of calls per hour is not far away. The second is the proliveration of fast (multi-mega instructions per second) computer systems and sophisticated operation systems (OSs). And finally, there is the consistent progress in the development of standard protocols between network users and service access entities, and between the service entities distributed in the network. However, the control (i.e., routing and access-control) of services in an ISN environment is a fundamental problem that has, until recently, attracted little attention in the literature.
The Public Switched Telephone Network (PSTN) of today is designed for a relatively static traffic environment: 3 Khz of bandwidth; 3 minute average holding time; and 3 CCS (hundred call seconds per hour) busy hour traffic per line. Accordingly, traffic control policies in the PSTN are static and open-loop in nature. A typical traffic control procedure is as follows: the day is divided into a number of time periods, during which the traffic patterns are well understood, and a different set of pre-planned control schemes is devised for each period. Network management activities override the pre-planned control schemes in case of "rare" events such as failures or when traffic levels exceed the designed thresholds.
FIG. 1 is a block diagram of a typical network control structure presently in use. Such a system utilizes auxiliary automatic and manual control techniques for network management based on experience and intuition. Typically, the routing scheme for a given network is preplanned according to an expected offered load in a given period and for a given network topology. As shown in FIG. 1, weekly or bi-weekly traffic reports are analyzed in block 10, yielding predicted traffic demands which are optimized in box 12 to serve the network 14. Exception reports of rare events such as failures or major overloads are signaled from the network 14 to the network management 16, where they are examined and heuristic adjustments are made to the preplanned control policy of network 14.
A number of factors suggest that the static, open-loop method of network control may be inappropriate for the increasingly volatile homogeneous or heterogeneous traffic environments of the future. (i) The traffic demands on today s network are becoming more dynamic and less predictable as a result of (1) the introduction of a plethora of services such as Enhanced 800 and Private Virtual Networks; (2) erratic behavior of customer premises equipment (CPE) such as automatic redialers; and (3) structural changes to the message transport network such as the addition of a separate common channel signaling network.
For example, a network equipped with common channel signaling (CCS) capabilities may encounter a novel problem: when CCS is employed on a trunk group (TG), ineffective call attempts can potentially be disposed of in as little as 125 milliseconds (or 28,800 calls per hour per circuit) as opposed to 20 seconds (or 180 calls per hour per circuit) for calls that are handled using in-band signaling. The enormous expansion of the domain of possible arrival rates leads naturally to a more volatile traffic environment.
(ii) The present day telecommunication network, unlike the one of the past, does not operate in isolation; the profile of the internally generated traffic may be well understood but the characteristics of exogenous traffic, generated by neighboring Local Access Transport Areas (LATAs) or Inter-Exchange Carriers (ICs), may not.
(iii) Transient bursts in the load of particular services, even if short-lived, cannot be ignored anymore. (Brokers attempting to trade stocks during a market crash will testify to this!)
(iv) Long-term traffic demands for such services as multi-media connections (voice/data/video), multi-point connections, etc. are largely unknown. For example, if the ISN should provide the transport for Community Antenna TV (CATV), consider the challenge of forecasting set-up attempt rates due to customers switching TV channels on any given night.
(v) In the past network efficiency has been limited by the switching and transmission capacity of network elements (NEs). Consequently, networks were characterized by small trunk sections and high inter-exchange connectivities, resulting in a high degree of resiliency. Today, we can dramatically improve network efficiency, for example, by replacing a number of copper TGs with a single fiber optic cable. However, the transition to a more efficient network will sacrifice resiliency, if the network is controlled in the static open-loop mode.
In the past few years a number of dynamic routing schemes have been proposed, in part, to address some of the issues outlined above. The two foremost of these schemes are Dynamically Controlled Routing (DCR) and Dynamic Non-Hierarchical Routing (DNHR).
Dynamic routing methods adjust traffic flow in a network as a function of network states. The most advanced of these methods is Bell Northern Research's "Dynamically Controlled Routing" (DCR), described in "Dynamic Routing for Intercity Telephone Networks", W. H. Cameron et al., Proceeding of ITC-10, Montreal, 1983.
DCR is a centralized, adaptive routing scheme. In a network controlled by DCR, every originating call has a number of pre-defined routes (tandem and direct) which it can take to its destination, with tandem routes being comprised of two links. In the DCR environment the network exchanges periodically relay (every 10 seconds) trunk group (TG) utilization levels to a central network processor. Using the TG utilizations and capacities in conjunction with the pre-defined routing topology, the network processor computes a set of tandem recommendations, in the form of routing probabilities, for each source-destination (SD) pair in the network. The network processor then sends a set of tandem recommendations back to the exchanges to update their routing tables. The recommendations are based primarily on the excess capacity of the tandem routes at the time of measurement. Although the network processor possesses real-time, global state information, the routing decisions for each SD pair are made independently of all other pairs. The network exchanges use the tandem recommendations in the following manner: when a call arrives at a source exchange it is automatically offered to the direct route; if the direct route is full, one of the remaining tandem routes will be chosen based on the probabilities in the routing table.
A well-known routing algorithm, which is not a network management and control system, is "Dynamic Non-Hierarchical Routing" (DNHR), developed by Bell Laboratories. This algorithm is believed to be in operational use today in some networks. In its original form, DNHR does not operate in real-time. Furthermore, DNHR is not able to react to call-processor congestion and network element failure. Recently, DNHR has been enhanced with limited real-time routing capabilities, which are, in principle, similar to "Dynamic Controlled Routing" (DCR), described infra. DNHR is described by Ash et al., "Design and optimization of networks with dynamic routing", Bell System Technical Journal, pp. 1787-1820, October 1981. The enhanced DNHR is disclosed in U.S. Pat. No. 4,669,113. Enhanced DNHR is also believed to be operational in some networks.
DNHR is a time-dependent routing scheme which capitalizes on differing time zone trunk usage by dividing the day into 10 time periods and using a different set of pre-planned routing sequences for each time period. The routing sequences reflect the optimal routes for calls to complete upon, based upon extensive operational measurement data, which is periodically provided by each participating exchange to the central network management system. The routing tables and network configuration are reviewed and evaluated by a centralized automated data collection and processing system. This system evaluate the exchange data in weekly and semi-weekly periods. DNHR reacts to real-time overloads (signified by SD blockings exceeding certain thresholds) by altering the pre-planned routing sequences in a manner similar to DCR.
Supplementing routing algorithms discussed supra, auxiliary automatic and manual control techniques provide recommendations for network management based upon experience and intuition. Typically, the routing scheme for a given network is pre-planned according to an expected offered load in a given period and for a given network topology. The routing scheme is then designed accordingly to satisfy a nominal performance objective. Whenever the offered load exceeds the expected level or the network topology changes due to a failure, the pre-planned routing scheme must be altered accordingly; the auxiliary network control scheme assumes this responsibility. However the auxiliary network controller's routing policy is designed to alleviate the overload or the failure problem: it does not, and is not designed to recommend control policies which achieve the nominal routing objectives.
As the size and the complexity of networks grow, it becomes difficult, if not impossible, to solely rely on intuition for network management decisions. For a fully connected 10-node network there are 90 source-destination pairs. If there are 3 routes assigned for each pair, there will be 270 traffic routes that must be monitored and controlled simultaneously in real-time. For a 20-node network (with 3 routes per source-destination pair) there are 1140 traffic routes to be controlled simultaneously.
If routing decisions are based on heuristics, there is no guarantee that they are optimal or even desirable solutions to the problem. In a heuristic system, recommendations are derived in isolation from nominal routing objectives, such as minimum blocking.
Although the traffic routing schemes discussed above are, to a certain degree, capable of reacting to real-time changes in traffic patterns, neither is truly designed to operate in volatile or extreme traffic conditions. Both DCR and DNHR only allow the use of two-link routes and prefer direct routes. However, long routes (of three or more links are frequently used to bypass failures, and the customary notions of direct and alternate routes do not apply to volatile situations. In such conditions, both algorithms rely on network management activities for network control. However, these network management recommendations are based typically on heuristics that do not, in general, follow the nominal traffic control objectives. Another shortcoming of these algorithms is that they are designed for homogeneous traffic environments. Consequently they are inappropriate control strategies for the ISNs accommodating heterogeneous traffic.
The routing recommendations devised by DCR and DNHR are based on the instantaneous traffic conditions in the network. Thus, they react to volatile conditions, rather than avoid them.
The most recent patent from the evolving methods of DNHR, U.S. Pat. No. 4,788,721, Nov. 29, 1988, issued Krishnan et al., discloses a method for routing traffic over a voice network uses some state measurements and estimates of future blockings, but principally on a source-destination basis rather than on a network bases. Krishnan's routing scheme calculates source-destination arrival rates every 1/2 to 2 hours. Consequently, it cannot control real-time surges in traffic, and hence, it is not an appropriate control strategy for the highly volatile traffic environments of the ISNs. Krishnan's routing strategy is limited to the control of voice-only networks.
Krishnan's routing algorithm projects the short-term gain for each individual source-destination pair, as a function of routing. Consequently, Krishnan's routing algorithm (i) does not yield optimal network behavior, as different SD pairs may compete for network resources, as opposed to cooperate to achieve optimal network performance; (ii) is not able to control access to network resources in a manner so as to reject the less revenue-generating calls at the expense of the more expensive ones; (iii) has to measure link occupancy levels and compute the control strategy for each call. This is considered prohibitive overhead for today's or even the foreseeable future's network switches.